[SPARK-19636][ML] Feature parity for correlation statistics in MLlib

## What changes were proposed in this pull request?

This patch adds the Dataframes-based support for the correlation statistics found in the `org.apache.spark.mllib.stat.correlation.Statistics`, following the design doc discussed in the JIRA ticket.

The current implementation is a simple wrapper around the `spark.mllib` implementation. Future optimizations can be implemented at a later stage.

## How was this patch tested?

```
build/sbt "testOnly org.apache.spark.ml.stat.StatisticsSuite"
```

Author: Timothy Hunter <timhunter@databricks.com>

Closes #17108 from thunterdb/19636.

1 files changed, 8 insertions, 0 deletions

diff --git a/mllib-local/src/test/scala/org/apache/spark/ml/util/TestingUtils.scala b/mllib-local/src/test/scala/org/apache/spark/ml/util/TestingUtils.scala
index 2327917e2c..30edd00fb5 100644
--- a/mllib-local/src/test/scala/org/apache/spark/ml/util/TestingUtils.scala
+++ b/mllib-local/src/test/scala/org/apache/spark/ml/util/TestingUtils.scala
@@ -32,6 +32,10 @@ object TestingUtils {
    * the relative tolerance is meaningless, so the exception will be raised to warn users.
    */
   private def RelativeErrorComparison(x: Double, y: Double, eps: Double): Boolean = {
+    // Special case for NaNs
+    if (x.isNaN && y.isNaN) {
+      return true
+    }
     val absX = math.abs(x)
     val absY = math.abs(y)
     val diff = math.abs(x - y)
@@ -49,6 +53,10 @@ object TestingUtils {
    * Private helper function for comparing two values using absolute tolerance.
    */
   private def AbsoluteErrorComparison(x: Double, y: Double, eps: Double): Boolean = {
+    // Special case for NaNs
+    if (x.isNaN && y.isNaN) {
+      return true
+    }
     math.abs(x - y) < eps
   }